Zhen Liu

A Secure and Practical Blockchain Scheme for IoT

2019

With features such as decentralization, consistency, tamper resistance, non-repudiation, and pseudonym, blockchain technology has the potential to strengthen the Internet of Things (IoT) significantly, thus opening an intriguing research area in the integration of blockchain …

Link-Information Augmented Twin Autoencoders for Network Denoising

2022 · IEEE Transactions on Cybernetics

Removing noisy links from an observed network is a task commonly required for preprocessing real-world network data. However, containing both noisy and clean links, the observed network cannot be treated as a trustworthy information source …

Multi-graph Convolutional Feature Transfer for Cross-domain Recommendation

2022 · 2022 International Joint Conference on Neural Networks (IJCNN)

Cross-domain recommendation(CDR) is an effective method to alleviate the data sparsity problem in the recommendation system. How to learn common and domain-specific feature embeddings of users and items is a challenge especially where the two …

Meta-Learning for Debiasing Recommendation using Simulated Uniform Data

2024

The recommendation system is subject to various biases, resulting in different training and testing data distribution. Most previous work either relies on a part of uniform data to guide model training which is difficult to …

Kinect Sensor and Improved ResNet-34 Model for the Design of a Precision Training Information Sharing Platform for Vocational Skills

2024

The development of technologies such as computers and artificial intelligence provides excellent technical support for the construction of precise vocational skills training platforms. In order to facilitate the sharing of vocational skills training information and …

Event-Based Intelligent Sensitivity Analysis and Performance Prediction With Application to Hydraulic System Monitoring

2024

This study proposes an intelligent sensitivity analysis and performance prediction approach for complex systems based on novel integration of event clustering and random forest regression techniques. The event clustering method is used for real-time sensitivity …

FDAGCL:Feature Discrepancy-Aware Graph Contrastive Learning

2026 · Neural Processing Letters

In recent years, Graph Contrastive Learning (GCL) has emerged as a key research direction for learning representations of unlabeled graph data, focusing on the self-supervised learning of efficient representations for both graphs and nodes. However, …